2012 ©
Journal Publication
Title of Article Self-adaptive many-objective meta-heuristic based on decomposition for many-objective conceptual design of a fixed wing unmanned aerial vehicle 
Date of Acceptance 12 February 2020 
     Title of Journal Aerospace Science and Technology 
     Standard ISI 
     Institute of Journal Elsevier Masson 
     ISBN/ISSN 12709638 
     Volume 2020 
     Issue 100 
     Month May
     Year of Publication 2020 
     Abstract Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for further decision making. In this paper, a many-objective optimisation problem for an unmanned aerial vehicle (UAV) is posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints. Aerodynamic analysis is carried out using a vortex lattice method, while aircraft component weights are estimated empirically. A new self-adaptive meta-heuristic based on decomposition is specifically developed for this design problem. The new algorithm along with nine established and recently developed multi-objective and many-objective meta-heuristics are employed to solve the problem, while comparative performance is made based upon a hypervolume indicator. The results reveal that the proposed optimiser is the best performer for this design task. 
     Keyword Aircraft conceptual design, Many-objective optimisation, Aircraft performance, Dynamic stability 
617040006-9 Mr. PAKIN CHAMPASAK [Main Author]
Engineering Doctoral Degree

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Level of Publication นานาชาติ 
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